Abstract
Wireless sensor network (WSNs) contribute significantly to emerging areas such as ubiquitous computing, smart systems, and the Internet of Things. A WSN is a highly distributed network of tiny sensors that are self-conscious and are deployed in different locations around the globe for various applications. These tiny sensors face resource problems in terms of power consumption, processing speed, communication range, and available bandwidth, etc. To protract the lifetime of a WSN, efficient and smart usage of available resources is very important. Therefore intelligent/effective resource management is a complex job which includes resource discovery/identification, resource scheduling, resource allocation, resource provisioning, resource sharing, resource utilization, and resource monitoring in the networks. Computational intelligent techniques are a highly efficient tool to address the critical issues and challenges of WSNs. These techniques include artificial intelligence, bioinspired techniques, machine learning, fuzzy logic, game theory, genetic algorithms, cognitive agents, and so on.
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